The magnetometer sensor on a spinning projectile is used to determine the projectile roll aspect angle with respect to the earth magnetic vector. Modern smart weapon technology requires great accuracy from this and similar sensors. The magnetic sensor requires relatively high-gain, low noise circuitry in order to produce clean, reliable magnetic vector crossing data to the on-board processor.
The high gain requirement of the magnetic sensor renders it susceptible to corrupting interference from a number of outside sources. The sources of interference can range from on-board currents and voltages, electromagnetic radiation within the projectile, unintentional off-board electromagnetic radiation emitters, and intentional disruptive sources.
Therefore, a need arises for a digital signal processing (DSP) autocorrelation algorithm that would significantly reduce the corrupting effects of interference. The algorithm would perform its sensing task, while being compact, computationally efficient. It would utilize mostly simple binary operations and some limited integer mathematics. As such, the algorithm would be highly time-efficient, with minimal impact on limited on-board computational and energy resources. The need for such a DSP autocorrelation algorithm has heretofore remained unsatisfied.